1. Field of the Invention
The present invention relates to the processing of individual choices to produce expedited and accurate collective outcomes. More specifically, the present invention relates to a system and method for overcoming decision-making and communications errors to produce expedited and accurate group choices.
2. Related Art
In the past, wired and wireless networks have been used to process individual choices or votes into collective outcomes in decision rooms, surveys, polls, and other collective decisions. However the software systems used in such applications are not designed to withstand communication errors, do not enable a group to reach a consensus even though all of the votes have not been received for processing, and do not weight individual votes on one or more dimensions of choice to maximize the group probability of making one or more correct or optimal collective decisions. As such, these problems limit the reliability and accuracy of group decisions.
Communication errors can be caused in numerous ways, including malicious physical or cyber attacks against the network and equipment failure (e.g., link or node failure in the network). In the case of wired networks, destroying or damaging the nodes or links in the network can delay and/or thwart the delivery of votes to be processed into collective outcomes. Cyber attacks can use computer viruses or worms to destroy software systems and/or data required in the collection and processes of individual choices into collective outcomes. These attacks can include viruses that overload node capacity (creating DOS (Denial of Service) effects) or network links (creating network errors in connecting to destination nodes), as well as intrusions that occur when authentication, encryption, server management tools, and other security techniques are penetrated.
Communication breakdowns can also be caused by so-called “benign” or inadvertent errors that occur because the programming tools used to create the software systems contain loopholes or faults that can lead to malfunctions in the submission and processing of votes. These types of errors will not only produce counting errors that are likely to go undetected and uncorrected, but also provide an opportunity for malicious actions to take place (see, e.g., F. B. Schneider, G. Morrisset, and R. Harper, “A Language-Based Approach To Security”, in R. Wilhelm ed., Informatics: 10 Years Back, 10 Years Ahead, Lecture Notes in Computer Science, Volume 2000 Springer-Verlag, Heidelberg, 2000). For example, when a buffer overflow occurs in submitting data to a database, the error provides an opening that can be exploited by an individual or software process to gain access to the database to change, destroy, and/or damage data.
Benign errors can also be caused by noise created when transmitter power levels and the number of terminals are not optimized for sending data to a wireless base station. (see, e.g., D. Goodman, Zory Marantz, Penina Orenstein, Virgilio Rodriguez “Maximizing the Throughput of CDMA Data Communications,” http://utopia.poly.edu/˜vrodri01/papers/vtc_gmpr03.pdf.)
Although malicious and benign errors can occur in wired and wireless networks, both types of errors have a greater impact in wireless networks than they do in wired networks. In wired networks, for example, adaptive routing can enable the votes to be submitted successfully despite physical attacks on particular nodes or links in the network. Similarly, the greater processing power and energy capacity of wired nodes enables the use of intrusion detection and correction software to counter cyber attacks. In contrast, in wireless networks, connectivity is not is as flexible or responsive and mobile devices lack the processing and energy capacity to adapt to the challenges posed by malicious and benign communications errors.
In these fragile communications environments, both types of errors can have deleterious effects on the ability of groups to reach a consensus and/or to produce an accurate collective choice. These effects can make it impossible for a group to agree and take action and/or produce a collective outcome that provides one or more correct or optimal choices to be carried out. In the first case, for example, malicious and/or benign communications errors may make it impossible to collect enough votes to determine if there is a majority consensus. Even if the aggregation rule is plurality, not majority, missing data may make it impossible to determine if the current plurality winner would be the eventual winner if it were possible to collect and count all the votes. In such cases, the group would not be able to take action to protect itself or to participate as part of a broader collective action to achieve particular objectives. The resulting loss of money, property, and life can be tremendous. In the second case, when the group is charged with reaching a consensus to find correct or optimal answers to one or more decision tasks, benign and malicious communications errors can have a filtering effect that prevents the most competent voters from submitting their votes, thereby allowing the collective decision to be dominated by the least competent voters. Collective incompetence also entails significant losses.
Even when malicious and benign communications errors do not present obstacles to processing individual choices into collective outcomes, time constraints can make slowly-produced collective outcomes irrelevant. For example, if a group of investors cannot reach a consensus before a deadline passes, they will miss an opportunity. Similarly, if a network of military decision makers cannot expeditiously reach a consensus about the capabilities of an approaching adversarial force, they may lose many lives—including their own. In both of these examples, the decision tasks may involve the selection of one or more correct or optimal choices. For instance, if the investors reach a consensus in time, but their collective outcome is wrong, they may not maximize the benefits derived from the opportunity. In fact, the investors may experience a disastrous loss instead of even a modest gain. Similarly, if the military decision makers produce collective outcomes that are very accurate, they may save many lives. However, as the accuracy of their collective decisions declines, the number of casualties will rise.
Another limitation of the state of the art is the exclusive focus on producing winning coalitions or decisive collective outcomes. Whether collective outcomes are constrained by time or malicious and/or benign communications errors, knowing if there is going to be a tie or an indecisive collective outcome can enable decision makers to take immediate action to collect additional information and/or follow contingency measures to minimize losses. For example, a tie produced by the default one person, one vote and plurality aggregation rule method may be resolved by applying an alternative method. If the voters rated all of the choices on an ordinal preference scale before voting for their most preferred choice, the rating data can be reprocessed under Condorcet scoring (based on binary contests among all of the choices across voter preference orderings), and the tie can be assessed to determine if one (or more) of the tied outcomes is a Condorcet winner. Knowing if there will be no collective consensus also provides an opportunity to launch a followup query to see if the group can reach a consensus on a different decision task.
State-of-the-art systems and methodologies for collecting information about individual preferences and judgments do not include voting mechanisms for dealing with communications and/or decision-making errors, nor can they adequately deal with emergencies or urgent time constraints. For example, polling and survey software does not include such mechanisms, nor do decision rooms with Group Decision Support Systems (GDSS) tools. GDSS tools rely on human facilitators, who cannot process information quickly and accurately enough—even with a GDSS—to address error and time constraints. Even when moderate time constraints allow a human to facilitate the production of a collective outcome, GDSS systems and methodology is limited by one-dimensional data collection and analysis and limitations on file functionality. Moreover, GDSS's require users who are relatively computer-savvy and comfortable using different computer tools. Further, GDSS quality is limited by difficulties in recruiting and retaining skilled facilitators (see, e.g., R. Chapman, “Helping The Group to Think Straight,” Darwin Magazine, August, 2003).
Current GDSS, polling, and survey solutions are also limited because they are not designed to process voice and/or gesture information as voting inputs or outputs. For example, although analog and digital voice technology is used to authenticate participants in a collective decision, they are not used to communicate information in novel ways to take advantage of the efficiency and effectiveness of representing preferences and/or judgments in digital and/or analog form. For example, voting by representing preferences by a preference range can provide richer input information than simply selecting a single point along a scale. Moreover, when individual analog inputs are processed to produce a collective outcome, the results can provide a more accurate and easily-computed view of the voting results.
Voice voting is a very “noisy” means of measuring preferences. For this reason, voting protocols such as Roberts Rules of Order only describe its use in binary decisions in which the “yays” can be readily distinguished from the “nays.” Still, voting theorists such as Condorcet recommended avoiding voice votes and Roberts Rules of Order prescribes the use of other voting mechanisms (show of hands, division of the whole, and/or ballot) to scrutinize the voice outcomes. Digital expression of voice votes can be used to improve the efficiency and accuracy of voice voting. Although voice votes could still be interpreted in analog mode, digitized voice inputs would integrate authentication (via techniques such as voice prints) with representation of intensity of preference based on pre-existing profiles that reveal personal ranges of intensity for each individual. Processing such inputs would make it unnecessary to clarify the outcomes of voice votes by using division of the whole, show of hands, or ballots.
Another limitation of the state of the art is the circumscribed use of mobile sensors in collective decision making. Currently, sensors report readings for environmental agents to a host machine where the data are aggregated to generate a report. Methodological and system constraints limit the precision and accuracy of the reports because simple distributional statistics must be used to describe phenomena. Sensors are not used to submit ratings based as if they were human decision makers expressing a preference over a list of choices or rendering a binary or rendering a binary or more complex judgment based rules of artificial intelligence for generating these preferences and/or judgments. Communications errors and malfunctions of sensors are two reasons that sensor collective decisions have not been developed.
The distribution and management of electricity in national network grids is a serious problem that produces blackouts that cause significant economic harm and dislocation. Although recent problems seem to have been caused by “benign” errors associated with overloading nodes and links, solutions to these problems have focused on attenuating errors and restabilizing the transmission of electricity once networks have broken down. What is needed is a flexible methodology and system to prevent network breakdowns from occurring. This solution would allow the network to sustain the flow of throughput and minimize vulnerability to destabilizing events. This type of solution is important for dealing with terrorists who could initiate cascading “benign” errors into a malicious cyber attack on the United States.
Accordingly, what would be desirable, but has heretofore not been provided, is a system and method for overcoming decision-making and communications errors to produce expedited and accurate group choices, which overcomes the aforementioned shortcomings.